Title :
Rotor fault diagnosis in a Squirrel-Cage Induction Machine using support vector
Author :
Hamdani, S. ; Mezerreg, H. ; Boutikar, B. ; Lahcene, N. ; Touhami, O. ; Ibtiouen, R.
Author_Institution :
Res. Lab. of Electrotechnics, Algiers, Algeria
Abstract :
This paper deals with the diagnosis of electrical defects of Squirrel-Cage Rotor Induction Machines (IMs). The failures of induction machine and the diagnosis methods are presented. Among the methods, Motor Current Signature Analysis (MCSA) is used in the experimental study to detect broken rotor bars and end-ring segment. The load level and the load effects on the diagnosis are also studied. Support vector machines (SVM) is applied to classify faults.
Keywords :
electric machine analysis computing; fault diagnosis; rotors; squirrel cage motors; support vector machines; broken rotor bars; end-ring segment; load effects; load level; motor current signature analysis; rotor fault diagnosis; squirrel cage induction machine; support vector machines; Induction motors; Kernel; Rotors; Stators; Support vector machine classification; Induction machine; classification; diagnosis; rotor faults; spectral analysis; support vector machines;
Conference_Titel :
Electrical Machines (ICEM), 2012 XXth International Conference on
Conference_Location :
Marseille
Print_ISBN :
978-1-4673-0143-5
Electronic_ISBN :
978-1-4673-0141-1
DOI :
10.1109/ICElMach.2012.6350128
